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Abstract

Generative Artificial Intelligences (AIs) and current advanced large language models (LLMs) are algorithmically designed to generate text-based conversations as conversational agents (CAs), by replicating human language and conversational communication. Pairing human cognition with generative computationally coded cognition. We have never been here before: cerebral and artificial information collaborations and processing producing expressions that may or may not become visible as second-hand/secondary source documents.

Sensemaking or sense(un)making is a unique autonomous human drive cognitively, our information processing is sensemaking in action and expressions and articulations are evidence of the sensemaking cycle. Documentation [expressed or articulated through various mediums] are a product of sensemaking. Framing information as relationships, we conceive of information processes as relational, e.g., seeking, scanning, monitoring, avoiding, retrieving, acquiring, creating, and disseminating information are incentivized by the sensemaking drive.

When we explore artificial information collaborations, we are looking for clues to the relationality of cerebral and computational information processing and asking if there is evidence that these “agents” support the human sensemaking cycle, and how to make the (in)visible visible to theorize information relationships of the artificial kind? The following paper rigorously examines the differentiation of human versus artificial cognitive information processes through linguistics/language, emotion/psychology, and reason/rationality to answer five theoretical questions.

Digital Object Identifier (DOI)

10.35492/docam/12/2/17

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